Weighted finite automata for video compression

Weighted finite automata (WFA) exploit self-similarities within single pictures and also sequences of pictures to remove spatial and temporal redundancies. Their implementation then combines techniques from hierarchical methods related to quadtrees and from vector quantization to achieve performance results for low bit rates which can be put on a par with state-of-the-art codecs like embedded zero-tree wavelet coding. Due to their simple mathematical structure, WFA provide an ideal platform for efficient hybrid compression methods. Therefore, WFA were chosen as a starting point for a fractal-like video compression integrating a hierarchical motion compensation as well as an option to vary the compression quality between “centers of interest” and “background” in a flexible manner